Leveraging Paired ‘Omics Datasets to Gain Insight into Actinomycete Natural Product Biosynthesis and Gene Cluster Distribution

Streptomyces bacteria have a remarkable capacity to biosynthesize natural products. The discovery of streptothricin in 1942 led to a wave of Streptomyces pharmaceutical research. Though reisolation and declining structural novelty eventually led to an industrial exit, decreases in the cost of genomic sequencing have reinvigorated microbial natural products. The expansion of genetic data has shown that bacteria have a genetic biosynthetic capacity larger than has been reported chemically. Biosynthetic genes often form Biosynthetic Gene Clusters (BGCs) within bacterial genomes allowing bioinformatic-based biosynthetic predictions. Despite this, efforts to classify identified BGCs have shown that most relate to unknown chemistry. However, recent advances in bio- and chem-informatics tools have given the ability to collect and analyze large datasets of complex genomic and metabolomic data to elucidate this biochemical “Dark Matter”. Bioinformatics tools have simplified the identification and classification of BGCs. Similar advances in cheminformatic analyses such as molecular networking and open-source software have simplified the analysis of metabolomics datasets. Though connecting these disparate datasets can be difficult, pattern-based genome mining allows the classification of BGCs by comparing presence, absence patterns between BGCs and metabolites. This dissertation consists of six chapters for which the goal was to explore the biosynthetic capacity of marine actinomycetes using novel tools and methodologies. Chapter 2 is a meta-analysis of existing publications and public genetic data relating to the predominantly marine clade of Streptomyces, MAR4, with an emphasis on natural products from this clade. For chapter 3, 42 new MAR4 genomes were generated with paired metabolomics data. The diversity of MAR4 vanadium haloperoxidase and prenyltransferase genes was explored using bio- and chem-informatics tools with an emphasis on their role in biosynthesis. Chapter 4 describes the discovery of a novel bioactive metabolite from the MAR4 clade, indanopyrrole. In this work the indanopyrrole BGC is described and its distribution amongst known bacteria explored. Chapter 5 is a metabolomic survey of marine sediment actinomycetes and their response to hypoxia. In this work it is shown that Streptomyces Strain CNB-091 reduces extracellular iron using a small molecule electron shuttle. Chapter 6 is a conclusion chapter and explores the impact of this dissertation